• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1597-1608
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• 2016

Recently, a number of solutions were proposed to address the challenges and issues of vehicular networks. Vehicular Cloud Computing (VCC) is one of the solutions. The vehicular cloud computing is a new hybrid technology that has a remarkable impact on traffic management and road safety by instantly using vehicular resources. In this paper, we study an important vehicular cloud service, content-based delivery, that allows future vehicular cloud applications to store, share and search data totally within the cloud. We design a VCC-based system architecture for efficient sharing of vehicular contents, and propose a Hierarchical Hybrid Content Delivery scheme using Bloom Filter (H2CDBF) for efficient vehicular content delivery in Vehicular Ad-hoc Networks (VANETs). The performance of the proposed H2CDBF is evaluated through an analytical model, and is compared to the proactive content discovery scheme, Bloom-Filter Routing (BFR).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.419-421
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• 2018

Cloud vehicular networks are a promising paradigm to improve vehicular through distributing computation tasks between remote clouds and local vehicular terminals. Software-Defined Network(SDN) can bring advantages to Intelligent Transportation System(ITS) through its ability to provide flexibility and programmability through a logically centralized controlled cluster that has a full comprehension of view of the network. However, as the SDN paradigm is currently studied in vehicular ad hoc networks(VANETs), adapting it to work on cloud-based vehicular network requires some changes to address particular computation features such as task computation of applications of cloud-based vehicular networks. There has been initial work on briging SDN concepts to vehicular networks to reduce the latency by using the fog computing technology, but most of these studies do not directly tackle the issue of task computation. This paper proposes a Software-Defined Cloud-based vehicular Network called SDCVN framework. In this framework, we study the effectiveness of task computation of applications of cloud-based vehicular networks with vehicular cloud and roadside edge cloud. Considering the edge cloud service migration due to the vehicle mobility, we present an efficient roadside cloud based controller entity scheme where the tasks are adaptively computed through vehicular cloud mode or roadside computing predictive trajectory decision mode. Simulation results show that our proposal demonstrates a stable and low route setup time in case of installing the forwarding rules of the routing applications because the source node needs to contact the controller once to setup the route.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.238-240
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• 2018

Cloud vehicular networks are a promising paradigm to improve vehicular through distributing computation tasks between remote clouds and local vehicular terminals. Software-Defined Network(SDN) can bring advantages to Intelligent Transportation System(ITS) through its ability to provide flexibility and programmability through a logically centralized controlled cluster that has a full comprehension of view of the network. However, as the SDN paradigm is currently studied in vehicular ad hoc networks(VANETs), adapting it to work on cloud-based vehicular network requires some changes to address particular computation features such as task computation of applications of cloud-based vehicular networks. There has been initial work on briging SDN concepts to vehicular networks to reduce the latency by using the fog computing technology, but most of these studies do not directly tackle the issue of task computation. This paper proposes a Software-Defined Cloud-based vehicular Network called SDCVN framework. In this framework, we study the effectiveness of task computation of applications of cloud-based vehicular networks with vehicular cloud and roadside edge cloud. Considering the edge cloud service migration due to the vehicle mobility, we present an efficient roadside cloud based controller entity scheme where the tasks are adaptively computed through vehicular cloud mode or roadside computing predictive trajectory decision mode. Simulation results show that our proposal demonstrates a stable and low route setup time in case of installing the forwarding rules of the routing applications because the source node needs to contact the controller once to setup the route.

• Information and Communications Magazine
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• v.31 no.3
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• pp.103-116
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• 2014

This paper proposes the design of Vehicular Cyber-Physical Systems (called VCPS) based on vehicular cloud for smart road networks. Our VCPS realizes mobile cloud computing services where vehicles themselves or mobile devices (e.g., smartphones and tablets of drivers or passengers in vehicles) play a role of both cloud server and cloud client in the vehicular cloud. First, this paper describes the architecture of vehicular networks for VCPS and the delay modeling for the event prediction and data delivery, such as a mobile node's travel delay along its navigation path and the packet delivery delay in vehicular networks. Second, the paper explains two VCPS applications as smart road services for the driving efficiency and safety through the vehicular cloud, such as interactive navigation and pedestrian protection. Last, the paper discusses further research issues for VCPS for smart road networks.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.12
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• pp.449-454
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• 2014

While the era of driverless car has come, Vehicular Ad hoc NETwork(VANET) is getting important. Original VANET has a limit that cannot use computation power, storage space of On Board Unit(OBU) installed in a vehicle efficiently. VANET cloud computing(VCC) solves the limit to focus on using abilities of each vehicle. This article proposes VCC architecture for supplementing user addition and initial cloud creation that have been researched insufficiently.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5669-5684
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• 2018

The new mobile edge network architecture has been required for an increasing amount of traffic, quality requirements, advanced driver assistance system for autonomous driving and new cloud computing demands on highway. This article proposes a hierarchical cloud computing architecture to enhance performance by using adaptive data load distribution for buses that play the role of edge computing server. A vehicular dynamic cloud is based on wireless architecture including Wireless Local Area Network and Long Term Evolution Advanced communication is used for data transmission between moving buses and cars. The main advantages of the proposed architecture include both a reduction of data loading for top layer cloud server and effective data distribution on traffic jam highway where moving vehicles require video on demand (VOD) services from server. Through the description of real environment based on NS-2 network simulation, we conducted experiments to validate the proposed new architecture. Moreover, we show the feasibility and effectiveness for the connected car media service on highway.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.142-145
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• 2014

지금까지 교통사고 예방을 위한 도로 정보 등을 제공하기 위해 차량 간 통신 네트워크인 Vehicular Ad hoc NETwork (VANET)연구가 활발히 진행되어왔다. 그러나 각 자동차의 On board unit (OBU)의 계산 능력, 저장 공간 등을 효율적으로 사용하는 연구는 진행되어 오지 않았다. 2011년 Olariu et al. 가 cloud computing을 기존의 VANET에 적용하는 개념인 Autonomous Vehicular cloud[1]를 제시하면서 새로운 VANET 연구의 새로운 장을 열었다. 기존의 VANET연구는 지금까지의 각각의 자동차의 통신 성능을 높이는 것에 초점을 맞추었지만, 새로운 아이디어는 높아진 각 자동차의 능력을 효율적으로 이용하여, 유용하게 사용하는 것에 초점을 맞추었다. 이것은 Intelligent Transport System (ITS)의 구축에 한발 더 나아갈 수 있게 하였다. 그 이후 VANET cloud computing (VCC)에 관한 많은 연구들이 진행되었으나 보안적인 측면에서는 아직 연구가 미흡한 실정이다. 그래서 본 논문에서는 보안을 보완한 VCC 아키텍처를 제안한다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.4
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• pp.183-189
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• 2018

With the recent advancement of vehicle wireless communication technology, many vehicular clouds have been proposed. The existing research focused on cloud services through data collection based on vehicular networks of mobile V2V (Vehicle-to-Vehicle) and V2I (Vehicle-to-Infrastructure). In this paper, we present a vehicular datacenter model that utilizes the vehicle in the parking space as a resource for the datacenter. Also, we derive resource allocation strategy based on the expected execution time considering the leave rate of each vehicle in our vehicular datacenter model. Simulation results show that our proposed resource allocation strategies outperform the existing strategy in terms of mean execution time.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.11
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• pp.263-270
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• 2019

Vehicular cloud computing is a new emerging technology that can provide drivers with cloud services to enable various vehicular applications. A vehicular cloud is defined as a set of vehicles that share their own resources. Vehicles should collaborate with each other to construct vehicular clouds through vehicle-to-vehicle communications. Since collaborating vehicles to construct the vehicular cloud have different speeds, directions and locations respectively, the vehicular cloud is constructed in multi-hop communication range. Due to intermittent wireless connectivity and low density of vehicles with the limited resources, the construction of vehicular cloud with multi-hop communications has become challenging in vehicular environments in terms of the service success ratio, the service delay, and the transmitted packet number. Thus, we propose a multi-hop vehicular cloud construction protocol that increases the service success ratio and decreases the service delay and the transmitted packet number. The proposed protocol uses a connection time-based intermediate vehicle selection scheme to reduce the cloud failure probability of multi-hop vehicular cloud. Simulation results conducted in various environments verify that the proposed protocol achieves better performance than the existing protocol.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.383-403
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• 2021

With the development of mobile edge computing (MEC), some late-model application technologies, such as self-driving, augmented reality (AR) and traffic perception, emerge as the times require. Nevertheless, the high-latency and low-reliability of the traditional cloud computing solutions are difficult to meet the requirement of growing smart cars (SCs) with computing-intensive applications. Hence, this paper studies an efficient offloading decision and resource allocation scheme in collaborative vehicular edge computing networks with multiple SCs and multiple MEC servers to reduce latency. To solve this problem with effect, we propose a context-aware offloading strategy based on differential evolution algorithm (DE) by considering vehicle mobility, roadside units (RSUs) coverage, vehicle priority. On this basis, an autoregressive integrated moving average (ARIMA) model is employed to predict idle computing resources according to the base station traffic in different periods. Simulation results demonstrate that the practical performance of the context-aware vehicular task offloading (CAVTO) optimization scheme could reduce the system delay significantly.